Stochastic robustness synthesis applied to a benchmark control problem

Christopher I. Marrison, Robert F. Stengel

Research output: Contribution to journalArticlepeer-review

36 Scopus citations


Stochastic robustness synthesis is used to find compensators that solve a benchmark problem. The synthesis minimizes a robustness cost function that is the weighted quadratic sum of stochastic robustness metrics. These metrics — probability of instability, probability of actuator saturation, and probability of settling time violation — are estimated using Monte Carlo analysis. A simple search method minimizes the robustness cost by selecting values for the design parameters of a linear quadratic Gaussian regulator. The resulting compensators are robust, require low actuator authority, and compare well with previous designs.

Original languageEnglish (US)
Pages (from-to)13-31
Number of pages19
JournalInternational Journal of Robust and Nonlinear Control
Issue number1
StatePublished - 1995

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • General Chemical Engineering
  • Biomedical Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering


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